We have built an AR version of the world-acclaimed tabletop game Carcassonne, called cARcassonne, using Unity and for the Microsoft Hololens 2.

This project has been funded by the Crafoord Foundation, and it’s led by Arezoo Sarkheyli-Hägele, started in cooperation with the former Egocentric Interaction Research Group.
Publications
- David Kadish, Arezoo Sarkheyli-Hägele, Jose Font, Georg Hägele, Diederick C Niehorster, Thomas Pederson. Towards Situation Awareness and Attention Guidance in a Multiplayer Environment using Augmented Reality and Carcassonne.
- Wilken, Kevin Bjørn Roulund. Bachelor thesis (supervised by Jose Font). cARcassonne for Hololens 2 – Improving UX through UI.
- Winkler, W, and Ågren, Simon. Bachelor thesis (supervised by Jose Font). Gaze tracking: Implementing gaze tracking in cARcassonne.
cARcassonne gameplay features

AR board placement by user. Place the board wherever feels best!

Game start and main board UI.

Play cARcassonne!
Current lines of research:
-Player modeling in cooperative/competitive environments.
-Detecting player intention through gaze tracking and gameplay data.
-Guiding player attention for strategy tips.

Board and gamestate representation
The game state in cARcassonne is encoded as a graph of interconnected game elements that allows us to easily perform complex computation over the board.

A Convolutional Neural Network agent learns to play the game from gameplay data, and a situation model attempts to model the upcoming moves and flow of the game.
Gaze tracking
We capture player gaze while playing cARcassonne. This can be displayed as a heatmap over the board to clearly see which areas players focus their attention to.




